用变换器模型实现带节拍信息的音乐演奏量化
Beat-Based Rhythm Quantization of MIDI Performances
- 基于节拍与强拍信息构建统一符号表示
- 在钢琴和吉他数据上超越现有最佳性能
- 适合音乐生成与自动记谱研究者
我们提出一种基于变换器的节奏量化模型，融合节拍与强拍信息，将MIDI演奏转换为符合节拍对齐、可读性高的乐谱。设计了一种基于节拍的预处理方法，将乐谱与演奏数据统一为符号表示。优化了模型结构与数据表示，在钢琴与吉他演奏数据上进行训练，其在MUSTER指标上的表现优于当前最优方法。
原文摘要 · Abstract (English)
We propose a transformer-based rhythm quantization model that incorporates beat and downbeat information to quantize MIDI performances into metrically-aligned, human-readable scores. We propose a beat-based preprocessing method that transfers score and performance data into a unified token representation. We optimize our model architecture and data representation and train on piano and guitar performances. Our model exceeds state-of-the-art performance based on the MUSTER metric.
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